Displaying ndtv Graphics in Spotfire using TERR and JSViz
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1 Displaying ndtv Graphics in Spotfire using TERR and JSViz Introduction The R package ndtv provides a quick and simple means to create compelling interactive graphics. The following R Code: library(ndtv) data ( short.stergm.sim ) render.d3movie ( short.stergm.sim, output.mode = 'HTML' ) Will produce an HTML page that shows the following animation when viewed in a web browser: This article will describe how to embed and call the ndtv library inside Spotfire using TERR and display the output using JSViz:
2 Prerequisites There are a number of components that have to be in place: 1) TERR R This release enables graphics support. 2) TIBCO Spotfire Statistics Service running TERR This is required if you need to run the solution in the Spotfire Consumer or Business Author. 3) The ndtv and datasets packages installed in TERR. Use the command install.packages("ndtv") and install.packages("datasets") in the TERR Console. 4) JSViz extension v or newer. This can be downloaded from TIBCO Community here. Follow the instructions in the User Guide to install the extension. It is important to use the correct version as we will use new features that have recently been added. It will also be useful to have a basic understanding of how to setup Spotfire Data Functions, but we will try to explain the steps as simply as possible. Creating the R Code The basic R Code that we showed above will create a file on disk that contains everything needed to display the visualization in a modern web browser. If we look at the HTML file generated, the required JavaScript files and JSON data needed to draw the network are embedded in the file: <!DOCTYPE html> <html lang='en'> <head> <meta charset='utf-8'> <!-- css for styling the d3.slider lib --> <style type='text/css'>... </style> <!-- minimized d3.js library --> <script>... </script> <!-- minimized jquery js library --> <script>... </script>... </head> <body> <script> //INIT GRAPH DATA HERE var graphdata = {"render":[{"... }; var options = {"ndtv.version":"0.10.0, "}; //END GRAPH DATA INIT //Insert init JS Here $(function() { options.graphdata = graphdata; var graph = new ndtv_d3(options); }) </script> </body> </html> In order to use this code in JSViz we just need to encapsulate it within a Data Function that will return the above HTML into a Spotfire Document Property. From there, JSViz will take care of displaying the chart. Capturing the HTML Output Thankfully, the designers of ndtv provide an option filename = 'tempfilename' that allows us to specify where we want to write the generated HTML file. We will use the R function tempfile() to create a temporary file path, pass this to the render.d3movie() function and then return this data to Spotfire in a Document Property. JSViz will then have the HTML data it needs to draw the graph. So our R Code will look like this:
3 # get a data set data(short.stergm.sim) # create a temp file path htmlfilepath <- tempfile ( "ndtv_demo" ) # render the json into the temp file render.d3movie ( short.stergm.sim, filename = htmlfilepath, output.mode = 'HTML', script.type = 'embedded' ) htmlout <- readchar ( htmlfilepath, file.info(htmlfilepath)$size ) We are now ready to put the code into Spotfire. Spotfire Setup As a first step we will setup the Spotfire Data Function to call the R code and return the output as acreate Document Property with all the required HTML code embedded. We will then display this in JSViz. Creating the Data Function You will need to open Spotfire with some dummy data. We are not sending this data into our Data Function so it can be anything at all. Click on EditData Function Properties and the following dialog will appear: Click on Register New to bring up the Register Data Functions dialog and select R Script TIBCO Enterprise Runtime for R. The dialog will look as follows:
4 Enter a title for the Data Function, we used Create ndtv Video and add datasets and ndtv to the list of packages. Also uncheck the Allow caching options. In the script box enter the following R code: # get a data set data(short.stergm.sim) # create a temp file path htmlfilepath <- tempfile ( "ndtv_demo" ) # render the json into the temp file render.d3movie ( short.stergm.sim, filename = htmlfilepath, output.mode = 'HTML', script.type = 'embedded', launchbrowser = FALSE ) # Return the HTML output htmlout <- readchar ( htmlfilepath, file.info(htmlfilepath)$size ) Note that the last line is special to the Spotfire Data Function and tells Spotfire how the HTML data will be returned. Our dialog will now look like this: Switch to the Output Parameters tab and set the output to be returned in a variable called htmlout : Click Close. Spotfire will prompt you to save your new Data Function in the Library.
5 Inserting the Data Function Create a Document Property of type String to hold the HTML data. We called ours HTMLData. Now, on the Data Function Properties dialog, click on the Insert button, pick the Data Function you just created and the Edit Parameters dialog will appear. Select the Output tab and assign the output to the Document Property you created: Click OK to close the Edit Parameters dialog. Click on Refresh to run your Data Function and then check the Document Properties and you should see that it contains the HTML for the visualization. You will most likely have to copy the contents of the Property into Notepad to see it, due to the HTML content. Close the Data Function Properties dialog. We are now ready to setup JSViz to render the visualization.
6 JSViz Setup Adding a JSViz Visualization Click on the JSViz toolbar icon to add a JSViz visualization. By default JSViz will set the Data item to be the default visualization in the DXP file. This is fine for our demo as we will not use any of this data to generate the visualization. The next step is to add the HTML content from the Document Property HTMLData. Adding HTML Linked Content Open the properties for the JSViz visualization and navigate to the Library page. Add a Linked Content item called chart.html using the special syntax %%DocProp.HTMLData%%. Once added, the Library page should look like this: Configuring the page contents The last step is to tell JSViz to use our html content item to draw the page. Click on the JSViz Contents page, and use the arrow to add chart.html to the Used Content list.
7 At this point the visualization will appear in the JSViz window:
8 Adding a Refresh control Our example uses data created in R so the video output does not change over time. However in real-world situations it would be more likely that data would flow from Spotfire into R which would result in the JSON data being re-generated and the visualization redrawn. To simulate this behaviour, and to allow for the case where R reads the data from some external source, we will add a Refresh button to re-execute the Data Function. Adding a Refresh button Add a Text Area to the left of the visualization and click to edit the Text Area contents. Click on Insert Action Control. In the Action Control dialog, select Data Function, pick the Data Function created earlier and give it a suitable name such as Refresh Video. Click OK when done. Close the Text Area editor. Clicking the Refresh Video button will cause the JSViz visualization to update. Note that the layout algorithm used is not deterministic, so the layout of the items will most likely change every time the button is clicked.
9 Adding customization To demonstrate how to customize the end visualization we will add a slider to control how many time slices that video contains. We will also setup the visualization to update whenever this setting is changed, removing the need for the update button. Adding a NumSlices Document Property Create a new Integer Document Property with an initial value of 25. Update the Data Function configuration We need to tell the Data Function to use this new Document Property as an input parameter and update the R Code. We will also tell the Data Function to run automatically whenever the Document Property changes. Click on Edit Data Function Properties then click on Edit Script. Update the R Code to insert the highlighted lines: # create a temp file path htmlfilepath <- tempfile ( "ndtv_demo" ) # Set the slice parameters slice.par=list(start=0,end=numslices-1,interval=1, aggregate.dur=1,rule='latest') compute.animation(short.stergm.sim,slice.par=slice.par) # render the movie into the temp file Switch to the Input Parameters tab and add a new Input Parameter called NumSlices as shown: Save the changes and close the Edit Script dialog. Click on Edit Parameters. Assign the NumSlices input parameter to be fed from the NumSlices Document Property, and set the Refresh function automatically option as shown:
10 Save the changes and close the Data Function editor dialog. Update the Text Area We can now add a slider control to adjust the value of our NumSlices Document Property between 1 and 25. We can also remove the Refresh button as the visualization will automatically refresh when the slider is changed. Edit the Text Area and remove the Refresh button. Click on Insert Property Control and select Slider. In the Property Control dialog, select the NumSlices Document Property and select Numerical range with values from 1 to 25. Click OK when done. Add some text to describe the slider control and then close the Text Area editor. Moving the slider will now cause the JSViz visualization to update:
11 Wrap-Up We have looked at how to create a simple example of using the ndtv libraries and how to integrate this into Spotfire along with how to pass in parameters. Hopefully by using these steps as a starting point, you should be able to create your own interactive visualization inside Spotfire using your data.
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